{"title":"单位圆盘上的解析高斯函数:零缺席的概率","authors":"A. Kuryliak, O. Skaskiv","doi":"10.30970/ms.59.1.29-45","DOIUrl":null,"url":null,"abstract":"In the paper we consider a random analytic function of the form$$f(z,\\omega )=\\sum\\limits_{n=0}^{+\\infty}\\varepsilon_n(\\omega_1)\\xi_n(\\omega_2)a_nz^n.$$Here $(\\varepsilon_n)$ is a sequence of inde\\-pendent Steinhausrandom variables, $(\\xi_n)$ is a sequence of indepen\\-dent standard complex Gaussianrandom variables, and a sequence of numbers $a_n\\in\\mathbb{C}$such that$a_0\\neq0,\\ \\varlimsup\\limits_{n\\to+\\infty}\\sqrt[n]{|a_n|}=1,\\ \\sup\\{|a_n|\\colon n\\in\\mathbb{N}\\}=+\\infty.$We investigate asymptotic estimates of theprobability $p_0(r)=\\ln^-P\\{\\omega\\colon f(z,\\omega )$ hasno zeros inside $r\\mathbb{D}\\}$ as $r\\uparrow1$ outside some set $E$ of finite logarithmic measure. Denote$N(r):=\\#\\{n\\colon |a_n|r^n>1\\},$ $ s(r):=2\\sum_{n=0}^{+\\infty}\\ln^+(|a_n|r^{n}),$$ \\alpha:=\\varliminf\\limits_{r\\uparrow1}\\frac{\\ln N(r)}{\\ln\\frac{1}{1-r}}.$ The article, in particular, proves the following statements:\\noi 1) if $\\alpha>4$ then\\centerline{$\\displaystyle \\lim_{\\begin{substack} {r\\uparrow1 \\\\ r\\notin E}\\end{substack}}\\frac{\\ln(p_0(r)- s(r))}{\\ln N(r)}=1$;} \n\\noi2) if $\\alpha=+\\infty$ then\\centerline{$\\displaystyle 0\\leq\\varliminf_{\\begin{substack} {r\\uparrow1 \\\\ r\\notin E}\\end{substack}}\\frac{\\ln(p_0(r)- s(r))}{\\ln s(r)},\\quad \\varlimsup_{\\begin{substack} {r\\uparrow1 \\\\ r\\notin E}\\end{substack}}\\frac{\\ln(p_0(r)- s(r))}{\\ln s(r)}\\leq\\frac1{2}.$} \n\\noiHere $E$ is a set of finite logarithmic measure. The obtained asymptotic estimates are in a certain sense best possible.Also we give an answer to an open question from \\!\\cite[p. 119]{Nishry2013} for such random functions.","PeriodicalId":37555,"journal":{"name":"Matematychni Studii","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytic Gaussian functions in the unit disc: probability of zeros absence\",\"authors\":\"A. Kuryliak, O. Skaskiv\",\"doi\":\"10.30970/ms.59.1.29-45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the paper we consider a random analytic function of the form$$f(z,\\\\omega )=\\\\sum\\\\limits_{n=0}^{+\\\\infty}\\\\varepsilon_n(\\\\omega_1)\\\\xi_n(\\\\omega_2)a_nz^n.$$Here $(\\\\varepsilon_n)$ is a sequence of inde\\\\-pendent Steinhausrandom variables, $(\\\\xi_n)$ is a sequence of indepen\\\\-dent standard complex Gaussianrandom variables, and a sequence of numbers $a_n\\\\in\\\\mathbb{C}$such that$a_0\\\\neq0,\\\\ \\\\varlimsup\\\\limits_{n\\\\to+\\\\infty}\\\\sqrt[n]{|a_n|}=1,\\\\ \\\\sup\\\\{|a_n|\\\\colon n\\\\in\\\\mathbb{N}\\\\}=+\\\\infty.$We investigate asymptotic estimates of theprobability $p_0(r)=\\\\ln^-P\\\\{\\\\omega\\\\colon f(z,\\\\omega )$ hasno zeros inside $r\\\\mathbb{D}\\\\}$ as $r\\\\uparrow1$ outside some set $E$ of finite logarithmic measure. Denote$N(r):=\\\\#\\\\{n\\\\colon |a_n|r^n>1\\\\},$ $ s(r):=2\\\\sum_{n=0}^{+\\\\infty}\\\\ln^+(|a_n|r^{n}),$$ \\\\alpha:=\\\\varliminf\\\\limits_{r\\\\uparrow1}\\\\frac{\\\\ln N(r)}{\\\\ln\\\\frac{1}{1-r}}.$ The article, in particular, proves the following statements:\\\\noi 1) if $\\\\alpha>4$ then\\\\centerline{$\\\\displaystyle \\\\lim_{\\\\begin{substack} {r\\\\uparrow1 \\\\\\\\ r\\\\notin E}\\\\end{substack}}\\\\frac{\\\\ln(p_0(r)- s(r))}{\\\\ln N(r)}=1$;} \\n\\\\noi2) if $\\\\alpha=+\\\\infty$ then\\\\centerline{$\\\\displaystyle 0\\\\leq\\\\varliminf_{\\\\begin{substack} {r\\\\uparrow1 \\\\\\\\ r\\\\notin E}\\\\end{substack}}\\\\frac{\\\\ln(p_0(r)- s(r))}{\\\\ln s(r)},\\\\quad \\\\varlimsup_{\\\\begin{substack} {r\\\\uparrow1 \\\\\\\\ r\\\\notin E}\\\\end{substack}}\\\\frac{\\\\ln(p_0(r)- s(r))}{\\\\ln s(r)}\\\\leq\\\\frac1{2}.$} \\n\\\\noiHere $E$ is a set of finite logarithmic measure. The obtained asymptotic estimates are in a certain sense best possible.Also we give an answer to an open question from \\\\!\\\\cite[p. 119]{Nishry2013} for such random functions.\",\"PeriodicalId\":37555,\"journal\":{\"name\":\"Matematychni Studii\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Matematychni Studii\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30970/ms.59.1.29-45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Matematychni Studii","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30970/ms.59.1.29-45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
Analytic Gaussian functions in the unit disc: probability of zeros absence
In the paper we consider a random analytic function of the form$$f(z,\omega )=\sum\limits_{n=0}^{+\infty}\varepsilon_n(\omega_1)\xi_n(\omega_2)a_nz^n.$$Here $(\varepsilon_n)$ is a sequence of inde\-pendent Steinhausrandom variables, $(\xi_n)$ is a sequence of indepen\-dent standard complex Gaussianrandom variables, and a sequence of numbers $a_n\in\mathbb{C}$such that$a_0\neq0,\ \varlimsup\limits_{n\to+\infty}\sqrt[n]{|a_n|}=1,\ \sup\{|a_n|\colon n\in\mathbb{N}\}=+\infty.$We investigate asymptotic estimates of theprobability $p_0(r)=\ln^-P\{\omega\colon f(z,\omega )$ hasno zeros inside $r\mathbb{D}\}$ as $r\uparrow1$ outside some set $E$ of finite logarithmic measure. Denote$N(r):=\#\{n\colon |a_n|r^n>1\},$ $ s(r):=2\sum_{n=0}^{+\infty}\ln^+(|a_n|r^{n}),$$ \alpha:=\varliminf\limits_{r\uparrow1}\frac{\ln N(r)}{\ln\frac{1}{1-r}}.$ The article, in particular, proves the following statements:\noi 1) if $\alpha>4$ then\centerline{$\displaystyle \lim_{\begin{substack} {r\uparrow1 \\ r\notin E}\end{substack}}\frac{\ln(p_0(r)- s(r))}{\ln N(r)}=1$;}
\noi2) if $\alpha=+\infty$ then\centerline{$\displaystyle 0\leq\varliminf_{\begin{substack} {r\uparrow1 \\ r\notin E}\end{substack}}\frac{\ln(p_0(r)- s(r))}{\ln s(r)},\quad \varlimsup_{\begin{substack} {r\uparrow1 \\ r\notin E}\end{substack}}\frac{\ln(p_0(r)- s(r))}{\ln s(r)}\leq\frac1{2}.$}
\noiHere $E$ is a set of finite logarithmic measure. The obtained asymptotic estimates are in a certain sense best possible.Also we give an answer to an open question from \!\cite[p. 119]{Nishry2013} for such random functions.